Modelling Seasonal Mortality with Individual Data
Stephen J. Richards, Stefan J. Ramonat, Gregory T. Vesper and Torsten Kleinow.
Most studies of seasonal variation in mortality rely on aggregated death counts at population level. In this paper we use individual data to present a series of models for diﬀerent aspects of seasonal variation. The models are ﬁtted to a variety of international pensioner data sets and suggest a high degree of commonality across countries with diﬀerent climates and diﬀerent health systems. The power of individual life-history survival modelling allows the detection of seasonal patterns in even modest-sized portfolios. We measure the tendency for seasonal ﬂuctuationstoincreasewithage, and we again ﬁnd strong similarities between geographically distinct populations. We further ﬁnd that seasonal eﬀects are generally uncorrelated with gender, but that low-income pensioners can suﬀer greater seasonal swings than high-income ones. Finally, we propose a single-parameter measure for the extent to which winter mortality is a spike and summer mortality is a shallower trough, and show results for a variety of data sets.
seasonal mortality, excess winter mortality, survival model.